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08/07/2023
AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning
Continual lifelong learning is an machine learning framework inspired by...
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06/28/2023
GraSS: Contrastive Learning with Gradient Guided Sampling Strategy for Remote Sensing Image Semantic Segmentation
Self-supervised contrastive learning (SSCL) has achieved significant mil...
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04/14/2023
BCE-Net: Reliable Building Footprints Change Extraction based on Historical Map and Up-to-Date Images using Contrastive Learning
Automatic and periodic recompiling of building databases with up-to-date...
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12/08/2022
Alleviating neighbor bias: augmenting graph self-supervise learning with structural equivalent positive samples
In recent years, using a self-supervised learning framework to learn the...
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11/15/2022
Self-supervised remote sensing feature learning: Learning Paradigms, Challenges, and Future Works
Deep learning has achieved great success in learning features from massi...
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11/15/2022
False: False Negative Samples Aware Contrastive Learning for Semantic Segmentation of High-Resolution Remote Sensing Image
The existing SSCL of RSI is built based on constructing positive and neg...
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10/30/2022
STGC-GNNs: A GNN-based traffic prediction framework with a spatial-temporal Granger causality graph
The key to traffic prediction is to accurately depict the temporal dynam...
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10/19/2022
HAVANA: Hard negAtiVe sAmples aware self-supervised coNtrastive leArning for Airborne laser scanning point clouds semantic segmentation
Deep Neural Network (DNN) based point cloud semantic segmentation has pr...
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10/15/2022
Augmentation-Free Graph Contrastive Learning of Invariant-Discriminative Representations
The pretasks are mainly built on mutual information estimation, which re...
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04/10/2022
TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning
Do we on the right way for remote sensing image understanding (RSIU) by ...
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03/31/2022
Deformation and Correspondence Aware Unsupervised Synthetic-to-Real Scene Flow Estimation for Point Clouds
Point cloud scene flow estimation is of practical importance for dynamic...
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03/29/2022
Image Segmentation with Adaptive Spatial Priors from Joint Registration
Image segmentation is a crucial but challenging task that has many appli...
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03/04/2022
Weighted Simultaneous Algebra Reconstruction Technique (wSART) for Additive Light Field Synthesis
We apply an iterative weighting scheme for additive light field synthesi...
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12/04/2021
Overcome Anterograde Forgetting with Cycled Memory Networks
Learning from a sequence of tasks for a lifetime is essential for an age...
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11/23/2021
Reviewing continual learning from the perspective of human-level intelligence
Humans' continual learning (CL) ability is closely related to Stability ...
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11/21/2021
Learning by Active Forgetting for Neural Networks
Remembering and forgetting mechanisms are two sides of the same coin in ...
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06/30/2021
Curvature Graph Neural Network
Graph neural networks (GNNs) have achieved great success in many graph-b...
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06/20/2021
Remote Sensing Images Semantic Segmentation with General Remote Sensing Vision Model via a Self-Supervised Contrastive Learning Method
A new learning paradigm, self-supervised learning (SSL), can be used to ...
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03/31/2021
Generating Multi-scale Maps from Remote Sensing Images via Series Generative Adversarial Networks
Considering the success of generative adversarial networks (GANs) for im...
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03/02/2021
Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks
One of the key problems of GNNs is how to describe the importance of nei...
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11/26/2020
KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting
When considering the spatial and temporal features of traffic, capturing...
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11/26/2020
Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images
Detecting the changes of buildings in urban environments is essential. E...
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11/22/2020
AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting
Traffic forecasting is a fundamental and challenging task in the field o...
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10/19/2020
Hierarchical Paired Channel Fusion Network for Street Scene Change Detection
Street Scene Change Detection (SSCD) aims to locate the changed regions ...
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10/02/2020
Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples
With the development of deep learning, supervised learning methods perfo...
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09/28/2020
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification
Training a modern deep neural network on massive labeled samples is the ...
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09/17/2020
Urban Traffic Flow Forecast Based on FastGCRNN
Traffic forecasting is an important prerequisite for the application of ...
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07/13/2020
Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources
Earth observation resources are becoming increasingly indispensable in d...
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06/20/2020
A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting
Accurate real-time traffic forecasting is a core technological problem a...
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04/18/2020
DAPnet: A double self-attention convolutional network for segmentation of point clouds
LiDAR point cloud has a complex structure and the 3D semantic labeling o...
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03/07/2020
DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images
Change detection is a basic task of remote sensing image processing. The...
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02/20/2020
Deep Fusion of Local and Non-Local Features for Precision Landslide Recognition
Precision mapping of landslide inventory is crucial for hazard mitigatio...
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01/27/2020
Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification
Remote sensing image scene classification is a fundamental but challengi...
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12/19/2019
SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images
High-resolution remote sensing images (HRRSIs) contain substantial groun...
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12/19/2019
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation
Enabling a neural network to sequentially learn multiple tasks is of gre...
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10/29/2019
Adversarial Example in Remote Sensing Image Recognition
With the wide application of remote sensing technology in various fields...
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10/26/2019
MAP-Net: Multi Attending Path Neural Network for Building Footprint Extraction from Remote Sensed Imagery
Accurately and efficiently extracting building footprints from a wide ra...
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09/22/2019
Volume Preserving Image Segmentation with Entropic Regularization Optimal Transport and Its Applications in Deep Learning
Image segmentation with a volume constraint is an important prior for ma...
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03/26/2019
Probabilistic Load Forecasting via Point Forecast Feature Integration
Short-term load forecasting is a critical element of power systems energ...
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03/26/2019
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis
Short-term load forecasting (STLF) is essential for the reliable and eco...
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03/09/2019
Program Classification Using Gated Graph Attention Neural Network for Online Programming Service
The online programing services, such as Github,TopCoder, and EduCoder, h...
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12/25/2018
Adversarial Feature Genome: a Data Driven Adversarial Examples Recognition Method
Convolutional neural networks (CNNs) are easily spoofed by adversarial e...
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12/04/2018
Overcoming Catastrophic Forgetting by Soft Parameter Pruning
Catastrophic forgetting is a challenge issue in continual learning when ...
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11/27/2018
Understanding the Importance of Single Directions via Representative Substitution
Understanding the internal representations of deep neural networks (DNNs...
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11/12/2018
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
Accurate and real-time traffic forecasting plays an important role in th...
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11/06/2018
A New Analysis for Support Recovery with Block Orthogonal Matching Pursuit
Compressed Sensing (CS) is a signal processing technique which can accur...
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10/22/2018
Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection
The key factor of scene change detection is to learn effective feature t...
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08/04/2017
On the Selective and Invariant Representation of DCNN for High-Resolution Remote Sensing Image Recognition
Human vision possesses strong invariance in image recognition. The cogni...
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05/30/2017
RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data
Remote sensing image classification is a fundamental task in remote sens...
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05/19/2017